Abstract

Since their emergence within the past decade, which has seen wireless networks being adapted to enable mobility, wireless networks have become increasingly popular in the world of computer research. A Mobile Ad hoc Network (MANET) is a collection of mobile nodes dynamically forming a temporary network without the use of any existing network infrastructure. MANETs have received significant attention in recent years due to their easiness to setup and to their potential applications in many domains. Such networks can be useful in situations where there is not enough time or resource to configure a wired network. Ad hoc networks are also used in military operations where the units are randomly mobile and a central unit cannot be used for synchronization.
The shared media used by wireless networks, grant exclusive rights for a node to transmit a packet. Access to this media is controlled by the Media Access Control (MAC) protocol. The Backoff mechanism is a basic part of a MAC protocol. Since only one transmitting node uses the channel at any given time, the MAC protocol must suspend other nodes while the media is busy. In order to decide the length of node suspension, a backoff mechanism is installed in the MAC protocol. The choice of backoff mechanism should consider generating backoff timers which allow adequate time for current transmissions to finish and, at the same time, avoid unneeded idle time that leads to redundant delay in the network. Moreover, the backoff mechanism used should decide the suitable action to be taken in case of repeated failures of a node to attain the media. Further, the mechanism decides the action needed after a successful transmission since this action affects the next time backoff is needed.
The Binary exponential Backoff (BEB) is the backoff mechanisms that MANETs have adopted from Ethernet. Similar to Ethernet, MANETs use a shared media. Therefore, the standard MAC protocol used for MANETs uses the standard BEB backoff algorithms. The first part of this work, presented as Chapter 3 of this thesis, studies the effects of changing the backoff behaviour upon a transmission failure or after a successful transmission. The investigation has revealed that using different behaviours directly affects both network throughput and average packet delay. This result indicates that BEB is not the optimal backoff mechanism for MANETs.
Up until this research started, no research activity has focused on studying the major parameters of MANETs. These parameters are the speed at which nodes travel inside the network area, the number of nodes in the network and the data size generated per second. These are referred to as mobility speed, network size and traffic load respectively. The investigation has reported that changes made to these parameters values have a major effect on network performance.
Existing research on backoff algorithms for MANETs mainly focuses on using external information, as opposed to information available from within the node, to decide the length of backoff timers. Such information includes network traffic load, transmission failures of other nodes and the total number of nodes in the network. In a mobile network, acquiring such information is not feasible at all times. To address this point, the second part of this thesis proposes new backoff algorithms to use with MANETs. These algorithms use internal information only to make their decisions. This part has revealed that it is possible to achieve higher network throughput and less average packet delay under different values of the parameters mentioned above without the use of any external information.
This work proposes two new backoff algorithms. The Optimistic Linear-Exponential Backoff, (OLEB), and the Pessimistic Linear-Exponential Backoff (PLEB). In OLEB, the exponential backoff is combined with linear increment behaviour in order to reduce redundant long backoff times, during which the media is available and the node is still on backoff status, by implementing less dramatic increments in the early backoff stages. PLEB is also a combination of exponential and linear increment behaviours. However, the order in which linear and exponential behaviours are used is the reverse of that in OLEB. The two algorithms have been compared with existing work. Results of this research report that PLEB achieves higher network throughput for large numbers of nodes (e.g. 50 nodes and over). Moreover, PLEB achieves higher network throughput with low mobility speed. As for average packet delay, PLEB significantly improves average packet delay for large network sizes especially when combined with high traffic rate and mobility speed. On the other hand, the measurements of network throughput have revealed that for small networks of 10 nodes, OLEB has higher throughput than existing work at high traffic rates. For a medium network size of 50 nodes, OLEB also achieves higher throughput. Finally, at a large network size of 100 nodes, OLEB reaches higher throughput at low mobility speed. Moreover, OLEB produces lower average packet delay than the existing algorithms at low mobility speed for a network size of 50 nodes.
Finally, this work has studied the effect of choosing the behaviour changing point between linear and exponential increments in OLEB and PLEB. Results have shown that increasing the number of times in which the linear increment is used increases network throughput. Moreover, using larger linear increments increase network throughput.